Files
axolotl/tests/test_loaders.py
NanoCode012 aa1240acd8 fix: transformers deprecate load_in_Xbit in model_kwargs (#3205)
* fix: transformers deprecate load_in_Xbit in model_kwargs

* fix: test to read from quantization_config kwarg

* fix: test

* fix: access

* fix: test weirdly entering incorrect config
2025-10-16 16:07:27 +07:00

219 lines
7.3 KiB
Python

"""Module for `axolotl.loaders`."""
from unittest.mock import MagicMock
import pytest
from transformers import BitsAndBytesConfig, PreTrainedTokenizerBase
from transformers.integrations.deepspeed import is_deepspeed_zero3_enabled
from transformers.utils.import_utils import is_torch_mps_available
from axolotl.loaders import ModelLoader
from axolotl.utils.dict import DictDefault
from axolotl.utils.distributed import _get_parallel_config_kwargs
class TestModelsUtils:
"""Testing module for `axolotl.loaders`."""
def setup_method(self) -> None:
# load config
self.cfg = DictDefault(
{
"base_model": "HuggingFaceTB/SmolLM2-135M",
"model_type": "AutoModelForCausalLM",
"tokenizer_type": "AutoTokenizer",
"load_in_8bit": True,
"load_in_4bit": False,
"adapter": "lora",
"flash_attention": False,
"sample_packing": True,
"device_map": "auto",
}
)
self.tokenizer = MagicMock(spec=PreTrainedTokenizerBase)
self.inference = False
self.reference_model = True
# init ModelLoader
self.model_loader = ModelLoader(
cfg=self.cfg,
tokenizer=self.tokenizer,
inference=self.inference,
reference_model=self.reference_model,
)
def test_set_device_map_config(self):
# check device_map
device_map = self.cfg.device_map
if is_torch_mps_available():
device_map = "mps"
self.model_loader._set_device_map_config()
if is_deepspeed_zero3_enabled():
assert "device_map" not in self.model_loader.model_kwargs
else:
assert device_map in self.model_loader.model_kwargs["device_map"]
# check torch_dtype
assert self.cfg.torch_dtype == self.model_loader.model_kwargs["torch_dtype"]
@pytest.mark.parametrize("adapter", ["lora", "qlora", None])
@pytest.mark.parametrize("load_in_8bit", [True, False])
@pytest.mark.parametrize("load_in_4bit", [True, False])
@pytest.mark.parametrize("gptq", [True, False])
def test_set_quantization_config(
self,
adapter,
load_in_8bit,
load_in_4bit,
gptq,
):
# init cfg as args
self.cfg.load_in_8bit = load_in_8bit
self.cfg.load_in_4bit = load_in_4bit
self.cfg.gptq = gptq
self.cfg.adapter = adapter
self.model_loader._set_quantization_config()
if "quantization_config" in self.model_loader.model_kwargs or self.cfg.gptq:
assert not (
hasattr(self.model_loader.model_kwargs, "load_in_8bit")
and hasattr(self.model_loader.model_kwargs, "load_in_4bit")
)
if self.cfg.adapter == "qlora" and load_in_4bit:
assert isinstance(
self.model_loader.model_kwargs.get("quantization_config"),
BitsAndBytesConfig,
)
assert (
self.model_loader.model_kwargs["quantization_config"]._load_in_4bit
is True
)
if self.cfg.adapter == "lora" and load_in_8bit:
assert isinstance(
self.model_loader.model_kwargs.get("quantization_config"),
BitsAndBytesConfig,
)
assert (
self.model_loader.model_kwargs["quantization_config"]._load_in_8bit
is True
)
def test_message_property_mapping(self):
"""Test message property mapping configuration validation"""
from axolotl.utils.schemas.datasets import SFTDataset
# Test legacy fields are mapped orrectly
dataset = SFTDataset(
path="test_path",
message_field_role="role_field",
message_field_content="content_field",
)
assert dataset.message_property_mappings == {
"role": "role_field",
"content": "content_field",
}
# Test direct message_property_mapping works
dataset = SFTDataset(
path="test_path",
message_property_mappings={
"role": "custom_role",
"content": "custom_content",
},
)
assert dataset.message_property_mappings == {
"role": "custom_role",
"content": "custom_content",
}
# Test both legacy and new fields work when they match
dataset = SFTDataset(
path="test_path",
message_field_role="same_role",
message_property_mappings={"role": "same_role"},
)
assert dataset.message_property_mappings == {
"role": "same_role",
"content": "content",
}
# Test both legacy and new fields work when they don't overlap
dataset = SFTDataset(
path="test_path",
message_field_role="role_field",
message_property_mappings={"content": "content_field"},
)
assert dataset.message_property_mappings == {
"role": "role_field",
"content": "content_field",
}
# Test no role or content provided
dataset = SFTDataset(
path="test_path",
)
assert dataset.message_property_mappings == {
"role": "role",
"content": "content",
}
# Test error when legacy and new fields conflict
with pytest.raises(ValueError) as exc_info:
SFTDataset(
path="test_path",
message_field_role="legacy_role",
message_property_mappings={"role": "different_role"},
)
assert "Conflicting message role fields" in str(exc_info.value)
with pytest.raises(ValueError) as exc_info:
SFTDataset(
path="test_path",
message_field_content="legacy_content",
message_property_mappings={"content": "different_content"},
)
assert "Conflicting message content fields" in str(exc_info.value)
@pytest.mark.parametrize(
"world_size, tensor_parallel_size, context_parallel_size, dp_shard_size, dp_replicate_size, is_fsdp, expected",
[
(16, 2, 2, 2, 2, True, (2, 2, 2, 2)),
(16, 1, 1, None, None, True, (0, 0, 16, 1)),
(16, 2, 2, 2, None, True, (2, 2, 2, 2)),
(16, 2, 2, None, 2, True, (2, 2, 2, 2)),
(16, 1, 1, None, 2, True, (0, 0, 8, 2)),
(2, 1, 1, None, None, True, (0, 0, 2, 1)),
],
)
def test_get_parallel_config_kwargs(
self,
world_size,
tensor_parallel_size,
context_parallel_size,
dp_shard_size,
dp_replicate_size,
is_fsdp,
expected,
):
res = _get_parallel_config_kwargs(
world_size,
tensor_parallel_size,
context_parallel_size,
dp_shard_size,
dp_replicate_size,
is_fsdp,
)
if expected[0] > 1:
assert res["tp_size"] == expected[0]
if expected[1] > 1:
assert res["cp_size"] == expected[1]
if expected[2] > 1:
assert res["dp_shard_size"] == expected[2]
if expected[3] > 1:
assert res["dp_replicate_size"] == expected[3]